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README.md
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### How to use
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Here is how to use this model:
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``` python
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from transformers import AutoTokenizer
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from transformers import AutoModelForCausalLM
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import torch
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input_text = 'Los alumnos atienden a sus profesores'
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print(translate_es_inclusivo(input_text))
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``` python
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As it is a heavy model, you may want to use it in 4-bits:
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``` python
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from transformers import AutoTokenizer
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from transformers import AutoModelForCausalLM
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from transformers import BitsAndBytesConfig
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input_text = 'Los alumnos atienden a sus profesores'
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print(translate_es_inclusivo(input_text))
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``` python
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## Training and evaluation data
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### How to use
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Here is how to use this model:
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+
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``` python
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+
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from transformers import AutoTokenizer
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from transformers import AutoModelForCausalLM
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import torch
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input_text = 'Los alumnos atienden a sus profesores'
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print(translate_es_inclusivo(input_text))
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``` python
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As it is a heavy model, you may want to use it in 4-bits:
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``` python
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+
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from transformers import AutoTokenizer
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from transformers import AutoModelForCausalLM
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from transformers import BitsAndBytesConfig
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input_text = 'Los alumnos atienden a sus profesores'
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print(translate_es_inclusivo(input_text))
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``` python
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## Training and evaluation data
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